- THIS ARTICLE
- Full Text (Rapid PDF)
-
All Versions of this Article:
genetics.106.055574v1
173/3/1511 most recent - Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via HighWire
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by Tanaka, M.
- Articles by Sisson, S.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by Tanaka, M.
- Articles by Sisson, S.
doi:10.1534/genetics.106.055574
A more recent version of this article appeared on July 1, 2006.
REGULAR RESEARCH PAPERS |
Estimating tuberculosis transmission parameters from genotype data using approximate Bayesian computation
Mark Tanaka 1*, Andrew Francis 2, Fabio Luciani 1 and Scott Sisson 1
1 University of New South Wales
2 University of Western Sydney
* To whom correspondence should be addressed. E-mail: m.tanaka{at}unsw.edu.au.
Submitted on January 8, 2006
Revised on April 5, 2006
Accepted on 5 April 2006
Tuberculosis can be studied at the population level by genotyping strains of Mycobacterium tuberculosis isolated from patients. We use an approximate Bayesian computational method in combination with a model of tuberculosis transmission and mutation of a molecular marker to estimate the nett transmission rate, the doubling time and the reproductive value of the pathogen. This method is applied to a published data set from San Francisco of tuberculosis genotypes based on the marker IS6110. The mutation rate of this marker has previously been studied, and we use those estimates to form a prior distribution of mutation rates in the inference procedure. The posterior point estimates of the key parameters of interest for these data are as follows: nett transmission rate, 0.69; doubling time, 1.09 years; and reproductive value 3.4. These figures suggest a rapidly spreading epidemic, consistent with observations of the resurgence of tuberculosis in the U.S. in the 1980s and 1990s.
Key Words: IS6110, Tuberculosis, approximate Bayesian computation, mutation rate, transmission
This article has been cited by other articles:
 |
|
 |
|
  D. A. Vasco A Fast and Reliable Computational Method for Estimating Population Genetic Parameters Genetics, June 1, 2008; 179(2): 951 - 963. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. A. Sisson, Y. Fan, and M. M. Tanaka Sequential Monte Carlo without likelihoods PNAS, February 6, 2007; 104(6): 1760 - 1765. [Abstract] [Full Text] [PDF]
|
|